Driving Personalization in Media and Entertainment

The emergence of generative AI has posed both opportunities and challenges for the media and entertainment industry. Whilst concerns around AI-generated content are often raised, there is also meaningful potential for the technology to vastly improve the customer experience.

Wherever you stand on the role of AI in creative output, it is clear that it has rapidly improved processes on the backend of streaming platforms and operationally within media and entertainment organizations. To harness the true power of the vast amount of data on hand within this industry, data governance is paramount.

Personalized Experiences, Powered by Governed Data

Data is an incredibly valuable asset within the media and entertainment ecosystem, where personalisation and engaging content are of high importance. Consequently, moving towards a unified and consistent approach to governance is essential, a sentiment echoed by 98% of CIOs across industries, according to a Databricks survey.

Audiences now crave, and in many cases expect, experiences tailored to their unique preferences. Achieving this level of personalisation requires a deep understanding of the audience, including content consumption preferences, engagement metrics, interest, demographics, purchase history and transaction data.

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Yet media organizations today grapple with a complex data landscape, where assets can be distributed across multiple systems, platforms and cloud environments. Data warehouses, data lakes and various other specialized tools each have their own governance models, creating silos and inconsistencies in data access, lineage and quality. This fragmentation poses significant challenges, hampering the ability to gain a comprehensive view of the audience and undermining the development of robust AI models that drive user engagement.

The Imperative of Unified Data Governance

For media and entertainment companies to respond to customer demand, effective data management is a strategic imperative. Poor data quality can significantly impact businesses, with firms lacking effective data practices estimated to waste up to 29% of their workforce’s time on unproductive tasks. Yet, it can be difficult to achieve C-suite buy-in for governance efforts, as they don’t directly boost revenue and can be time-consuming. Communicating their value is therefore paramount for IT professionals and leaders.

Equally, in today’s streaming-dominated landscape, media and entertainment organizations have access to more audience data than ever before. Consolidating information from disparate sources can enable organizations to develop comprehensive customer profiles, in turn unlocking generative AI models that deliver highly personalized content recommendations and tailored advertising. These models can only be truly accurate and deliver relevant outputs if the data that feeds them is well-governed. And, for organizations to comply with data privacy regulations, clear data lineage and traceability is vital.

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Establishing a Unified Data Governance Strategy

To realize the benefits of unified data governance, a top-down approach that is aligned with business objectives is essential. Chief data officers (CDOs) and chief AI officers can spearhead such initiatives, establishing an office of data management to define policies and a Data Council of leaders to set priorities and ensure compliance.

Organizations can start small, focusing on specific datasets such as those associated with customers or products. This targeted approach prevents the overwhelming scope of data governance from derailing the program. Equally, program leaders must demonstrate tangible business benefits throughout to maintain executive support. Successes should be regularly documented and included in broader communications that demonstrate the value of continued investment.

To support the full breadth of an organization’s needs, leaders can consider consolidating their analytics infrastructure into a single, enterprise-wide data environment, like a data intelligence platform. Such tools are built upon a unified vision for data analytics and have data governance embedded throughout, allowing engineers to ascertain insights from structured and unstructured data easily and at speed. This approach provides unified visibility into data and AI assets, a single permission model, built-in auditing and data quality enforcement, AI-powered monitoring and zero-copy data sharing across enterprises. In doing so, organizations can accelerate data and AI initiatives while simplifying regulatory compliance.

For organizations to keep up with the competition in a rapidly evolving media and entertainment landscape, robust data governance is essential. By adopting a unified, business-led approach and leveraging modern platforms, organizations can break down data silos, ensure transparency and trust in AI models, and ultimately deliver engaging, personalized content that captivates audiences and drives business success.